Fit AI-Personalized Diet and Fitness Planner
DOI:
https://doi.org/10.47392/IRJAEM.2025.0080Keywords:
Personalized Diet Planner, AI-Powered Fitness, Machine Learning, Streamlit, Mediapipe, Health Tracking, Adaptive Recommendations, Nutrition Guidance, Fitness Monitoring, Smart HealthcareAbstract
Maintaining a healthy lifestyle is becoming increasingly challenging due to hectic schedules, unhealthy eating habits, and the lack of personalized diet and fitness guidance. Generic health plans often fail to address individual requirements, leading to ineffective results and poor adherence. To overcome these challenges, FitAI: Personalized Diet and Fitness Planner is developed as an AI-powered web application that provides customized diet and fitness recommendations based on user-specific data. The system collects key user inputs, including age, height, weight, gender, exercise frequency, dietary preferences, and existing health conditions, to generate tailored health plans. By leveraging machine learning algorithms, FitAI analyzes this data to offer dynamic and adaptive suggestions that evolve based on user progress. Unlike static diet charts or generic fitness apps, FitAI continuously refines recommendations to match changing user needs. The application is developed using Python, Streamlit, and Mediapipe, ensuring a seamless, interactive, and intelligent user experience. Streamlit provides an intuitive web interface, simplifying user interactions, while Mediapipe enables real-time fitness tracking, ensuring correct posture and exercise execution. The AI-driven recommendation system continuously learns from user habits, improving the accuracy and relevance of health suggestions. The system was evaluated based on accuracy, efficiency, and user satisfaction, demonstrating a 90% alignment with expert health plans and 85% positive user feedback. The Mediapipe-based posture tracking effectively improved exercise form, while the Streamlit interface enhanced accessibility and engagement. However, challenges such as tracking accuracy variations and limited real-time health monitoring indicate areas for future improvement. FitAI bridges the gap between generic health recommendations and personalized wellness solutions, empowering individuals to take control of their fitness and nutrition. By integrating machine learning, adaptive AI models, and user-friendly web technologies, FitAI presents a smart, data-driven solution for individuals seeking effective and sustainable health management. Future enhancements may include integration with wearable devices and advanced deep learning models for more precise and real-time health tracking.
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Copyright (c) 2025 International Research Journal on Advanced Engineering and Management (IRJAEM)

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